A Cautionary Note on Modeling Growth Trends in Longitudinal Data

Autor/inn/en	Kuljanin, Goran; Braun, Michael T.; DeShon, Richard P.
Titel	A Cautionary Note on Modeling Growth Trends in Longitudinal Data
Quelle	In: Psychological Methods, 16 (2011) 3, S.249-264 (16 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1082-989X
DOI	10.1037/a0023348
Schlagwörter	Models; Trend Analysis; Longitudinal Studies; Regression (Statistics); Psychological Studies + Suchen Sie Ihr Suchwort? Analogiemodell; Trendanalyse; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Regression; Regressionsanalyse
Abstract	Random coefficient and latent growth curve modeling are currently the dominant approaches to the analysis of longitudinal data in psychology. The application of these models to longitudinal data assumes that the data-generating mechanism behind the psychological process under investigation contains only a deterministic trend. However, if a process, at least partially, contains a stochastic trend, then random coefficient regression results are likely to be spurious. This problem is demonstrated via a data example, previous research on simple regression models, and Monte Carlo simulations. A data analytic strategy is proposed to help researchers avoid making inaccurate inferences when observed trends may be due to stochastic processes. (Contains 4 figures, 2 footnotes and 4 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10